Literature DB >> 7304589

Confounding: essence and detection.

O S Miettinen, E F Cook.   

Abstract

Confounding is examined from first principles. In follow-up studies a confounder is a predictor of diagnosing the illness--by being either a risk indicator or a determinant of diagnostic errors; in addition, it shows different distributions between the exposed and nonexposed series. In case-referent studies confounding can arise in two ways. A priori confounders are correlates of exposure in the joint source population of cases and reference subjects; also, they are determinants of diagnosing the illness or have different selection implications between cases and referents. In addition, factors bearing on the accuracy of exposure information are confounders if distributed differently between cases and referents. Criteria based singularly on relationships in the data can be misleading. Similarly, a change in the estimate and even a change in the parameter as a result of control is not a criterion rooted in first principles of confounding and can lead to a false conclusion.

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Year:  1981        PMID: 7304589     DOI: 10.1093/oxfordjournals.aje.a113225

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  70 in total

1.  Confounding and confounders.

Authors:  R McNamee
Journal:  Occup Environ Med       Date:  2003-03       Impact factor: 4.402

2.  Impact of the availability of a prior electrocardiogram on the triage of the patient with acute chest pain.

Authors:  T H Lee; E F Cook; M C Weisberg; G W Rouan; D A Brand; L Goldman
Journal:  J Gen Intern Med       Date:  1990 Sep-Oct       Impact factor: 5.128

3.  The use and misuse of matching in case-control studies: the example of polycystic ovary syndrome.

Authors:  Michael S Bloom; Enrique F Schisterman; Mary L Hediger
Journal:  Fertil Steril       Date:  2007-04-11       Impact factor: 7.329

4.  Insights into different results from different causal contrasts in the presence of effect-measure modification.

Authors:  Til Stürmer; Kenneth J Rothman; Robert J Glynn
Journal:  Pharmacoepidemiol Drug Saf       Date:  2006-10       Impact factor: 2.890

Review 5.  Case-control studies in pharmacoeconomic research: an overview.

Authors:  J Jaime Caro; Krista F Huybrechts
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

6.  Time-modified confounding.

Authors:  Robert W Platt; Enrique F Schisterman; Stephen R Cole
Journal:  Am J Epidemiol       Date:  2009-08-12       Impact factor: 4.897

7.  On quantifying the magnitude of confounding.

Authors:  Holly Janes; Francesca Dominici; Scott Zeger
Journal:  Biostatistics       Date:  2010-03-04       Impact factor: 5.899

8.  The Simpson's paradox unraveled.

Authors:  Miguel A Hernán; David Clayton; Niels Keiding
Journal:  Int J Epidemiol       Date:  2011-03-30       Impact factor: 7.196

Review 9.  Why and how to control for age in occupational epidemiology.

Authors:  D Consonni; P A Bertazzi; C Zocchetti
Journal:  Occup Environ Med       Date:  1997-11       Impact factor: 4.402

10.  African American race and HIV virological suppression: beyond disparities in clinic attendance.

Authors:  Chanelle J Howe; Sonia Napravnik; Stephen R Cole; Jay S Kaufman; Adaora A Adimora; Beth Elston; Joseph J Eron; Michael J Mugavero
Journal:  Am J Epidemiol       Date:  2014-05-08       Impact factor: 4.897

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